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Record W2412117061

Capsule Endoscopy in the Assessment of Obscure Gastrointestinal Bleeding: An Economic Analysis.

2015· article· en· W2412117061 on OpenAlexaffabout
Stefan Palimaka, Gord Blackhouse, Ron Goeree

Bibliographic record

VenuePubMed · 2015
Typearticle
Languageen
FieldMedicine
TopicGastrointestinal Bleeding Diagnosis and Treatment
Canadian institutionsSt. Joseph’s Healthcare HamiltonPrograms for Assessment of Technology in Health Research Institute
Fundersnot available
KeywordsCapsule endoscopyMedicineEnteroscopyObscure gastrointestinal bleedingEsophagogastroduodenoscopyEndoscopyColonoscopyCapsulePopulationSurgeryGeneral surgeryInternal medicineEnvironmental health
DOInot available

Abstract

fetched live from OpenAlex

BACKGROUND: Small-bowel capsule endoscopy is a tool used to visualize the small bowel to identify the location of bleeds in obscure gastrointestinal bleeding (OGIB). Capsule endoscopy is currently funded in Ontario in cases where there has been a failure to identify a source of bleeding via conventional diagnostic procedures. In Ontario, capsule endoscopy is a diagnostic option for patients whose findings on esophagogastroduodenoscopy, colonoscopy, and push enteroscopy have been negative (i.e., the source of bleeding was not found). OBJECTIVES: This economic analysis aims to estimate the budget impact of different rates of capsule endoscopy use as a complement to push enteroscopy procedures in patients aged 18 years and older. DATA SOURCES: Population-based administrative databases for Ontario were used to identify patients receiving push enteroscopy and small-bowel capsule endoscopy in the fiscal years 2008 to 2012. REVIEW METHODS: A systematic literature search was performed to identify economic evaluations of capsule endoscopy for the investigation of OGIB. Studies were assessed for their methodological quality and their applicability to the Ontarian setting. An original budget impact analysis was performed using data from Ontarian administrative sources and published literature. The budget impact was estimated for different levels of use of capsule endoscopy as a complement to push enteroscopy due to the uncertain clinical utility of the capsule based on current clinical evidence. The analysis was conducted from the provincial public payer perspective. RESULTS: With varying rates of capsule endoscopy use, the budgetary impact spans from savings of $510,000, when no (0%) push enteroscopy procedures are complemented with capsule endoscopy, to $2,036,000, when all (100%) push enteroscopy procedures are complemented with capsule endoscopy. A scenario where 50% of push enteroscopy procedures are complemented with capsule endoscopy (expected use based on expert opinion) would result in additional expenditure of about $763,000. LIMITATIONS: In the literature on OGIB, estimates of rebleeding rates after endoscopic procedures or spontaneous cessation rates are unreliable, with a lack of data. Rough estimates from expert consultation can provide an indication of expected additional use of capsule endoscopy; however, a wide range of capsule uses was explored. CONCLUSIONS: The budgetary impact in the first year in Ontario of capsule endoscopy use to complement push enteroscopy procedures ranges from $510,000 in savings to an additional expenditure of $2,036,000 (at 0% and 100% push enteroscopy procedures complemented, respectively). The expected scenario of 50% of push enteroscopy procedures likely to benefit from the use of capsule endoscopy, based on expert opinion, would result in additional expenditures of $763,000 in the first year.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.021
metaresearch head score (Gemma)0.077
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.088
Threshold uncertainty score0.208

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.077
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.008
Bibliometrics0.0070.008
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.069
GPT teacher head0.319
Teacher spread0.250 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2015
Admission routes2
Has abstractyes

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